The mixing process plays a pivotal role in the design,optimization,and scale-up of chemical reactors.For most chemical reactions,achieving uniform and rapid contact between reactants at the molecular level is crucial....The mixing process plays a pivotal role in the design,optimization,and scale-up of chemical reactors.For most chemical reactions,achieving uniform and rapid contact between reactants at the molecular level is crucial.Mixing intensification encompasses innovative methods and tools that address the limitations of inadequate mixing within reactors,enabling efficient reaction scaling and boosting the productivity of industrial processes.This review provides a concise introduction to the fundamentals of multiphase mixing,followed by case studies highlighting the application of mixing intensification in the production of energy-storage materials,advanced optical materials,and nanopesticides.These examples illustrate the significance of theoretical analysis in informing and advancing engineering practices within the chemical industry.We also explore the challenges and opportunities in this field,offering insights based on our current understanding.展开更多
The present study introduces a screw-pressing charging method to tackle deficiencies in automation and charge uniformity during the melt-casting of polymer-based energetic materials.To ensure the safety of the experim...The present study introduces a screw-pressing charging method to tackle deficiencies in automation and charge uniformity during the melt-casting of polymer-based energetic materials.To ensure the safety of the experiments,this study used inert materials with similar physical properties to partially substitute for the actual energetic components in the preparation of simulant materials.By thoroughly analyzing slurry physical properties,a simulation framework and an extensive performance evaluation method were developed.Such tools guide the design of the structure and configuration of process parameters.Results demonstrate that employing the Pin element significantly enhances radial mixing within the screw,minimizes temperature variations in the slurry,and improves both efficiency and safety in the mixing process.Further,adjustments such as widening the cone angle of the barrel,modifying the solid content of the slurry,and varying the speed of the screw can optimize the mechanical and thermal coupling in the flow field.These adjustments promote higher-quality slurry and create a safer production environment for the extrusion process.展开更多
The implementation of ultrahigh-Ni cathodes in high-energy lithium-ion batteries(LIBs)is constrained by significant structural and interfacial degradation during cycling.In this study,doping-induced surface restructur...The implementation of ultrahigh-Ni cathodes in high-energy lithium-ion batteries(LIBs)is constrained by significant structural and interfacial degradation during cycling.In this study,doping-induced surface restructuring in ultrahigh-nickel cathode materials is rapidly facilitated through an ultrafast Joule heating method.Density functional theory(DFT)calculations,synchrotron X-ray absorption spectroscopy(XAS),and single-particle force test confirmed the establishment of a stable crystal framework and lattice oxygen,which mitigated H2-H3 phase transitions and improved structural reversibility.Additionally,the Sc doping process exhibits a pinning effect on the grain boundaries,as shown by scanning transmission electron microscopy(STEM),enhancing Li~+diffusion kinetics and decreasing mechanical strain during cycling.The in situ development of a cation-mixing layer at grain boundaries also creates a robust cathode/electrolyte interphase,effectively reducing interfacial parasitic reactions and transition metal dissolution,as validated by STEM and time-of-flight secondary ion mass spectrometry(TOF-SIMS).These synergistic modifications reduce particle cracking and surface/interface degradation,leading to enhanced rate capability,structural integrity,and thermal stability.Consequently,the optimized Sc-modified ultrahigh-Ni cathode(Sc-1)exhibits 93.99%capacity retention after 100 cycles at 1 C(25℃)and87.06%capacity retention after 100 cycles at 1 C(50℃),indicating excellent cycling and thermal stability.By presenting a one-step multifunctional modification approach,this research delivers an extensive analysis of the mechanisms governing the structure,microstructure,and interface properties of nickel-rich layered cathode materials(NCMs).These results underscore the potential of ultrahigh-Ni cathodes as viable candidates for advanced lithium-ion batteries(LIBs)in next-generation electric vehicles(EVs).展开更多
A reshock experiment for investigating the growth of material mixing driven by the Richtmyer–Meshkov instability has been conducted at the SG 100 kJ Laser Facility.We present a novel measurement technique for capturi...A reshock experiment for investigating the growth of material mixing driven by the Richtmyer–Meshkov instability has been conducted at the SG 100 kJ Laser Facility.We present a novel measurement technique for capturing the density field and the temporal evolution of the mixing width in rough aluminum subjected to reshocks under extreme conditions.The temporal evolution of the aluminum layer width obtained from backlit X-ray radiography demonstrates a sharp increase in width caused by reshocks,and simulations using the BHR-2 turbulent mixing model show excellent agreement with the measured aluminum layer width.Moreover,by utilizing a quasi-monochromatic X-ray imaging system at 5.2 keV,based on Bragg reflection from a spherically curved quartz crystal,we demonstrate direct quantification of the aluminum density field in mixed regions for the first time in a indirectly driven reshock experiment.The deviation between the calculated and actual density values is significantly less than 10%when the density of the aluminum region is below 0.7 g/cm3.The density field provides further information about variable-density turbulent mixing,which improves the constraints on simulations and enhances predictive capabilities for inertial confinement fusion target design and astrophysical shock scenarios.展开更多
Developing cost-effective single-crystalline Ni-rich Co-poor cathodes operating at high-voltage is one of the most important ways to achieve higher energy Li-ion batteries. However, the Li/O loss and Li/Ni mixing unde...Developing cost-effective single-crystalline Ni-rich Co-poor cathodes operating at high-voltage is one of the most important ways to achieve higher energy Li-ion batteries. However, the Li/O loss and Li/Ni mixing under high-temperature lithiation result in electrochemical kinetic hysteresis and structural instability. Herein, we report a highly-ordered single-crystalline LiNi0.85Co0.05Mn0.10O2(NCM85) cathode by doping K+and F-ions. To be specific, the K-ion as a fluxing agent can remarkably decrease the solid-state lithiation temperature by ~30°C, leading to less Li/Ni mixing and oxygen vacancy. Meanwhile, the strong transitional metal(TM)-F bonds are helpful for enhancing de-/lithiation kinetics and limiting the lattice oxygen escape even at 4.5 V high-voltage. Their advantages synergistically endow the single-crystalline NCM85 cathode with a very high reversible capacity of 222.3 mAh g-1. A superior capacity retention of 91.3% is obtained after 500 times at 1 C in pouch-type full cells, and a prediction value of 75.3% is given after cycling for 5000 h. These findings are reckoned to expedite the exploitation and application of high-voltage single-crystalline Ni-rich cathodes for next-generation Li-ion batteries.展开更多
In petroleum,mercaptan impurities generate malodorous fumes that pose risks to both human health and the environment,and leading to substandard oil quality.Lye desulfurization is a widely employed technique for elimin...In petroleum,mercaptan impurities generate malodorous fumes that pose risks to both human health and the environment,and leading to substandard oil quality.Lye desulfurization is a widely employed technique for eliminating mercaptans from oil.In traditional scrubber towers,lye and oil are poorly mixed,the desulfurization efficiency is low,and the lye consumption is high.To enhance washing efficiency,a droplet micromixer and corresponding fiber coalescence separator were developed.By optimizing the structure and operating parameters,more effective mixing and separation were achieved,and both caustic washing and desulfurization were enhanced.The proposed mixer/separator outperforms the industry standard by reducing the caustic loading by 30%and offers superior economic and engineering performances.The results of this study offer a direction for designing and optimizing a mercaptan removal unit to enhance the scrubbing effectiveness and decrease expenses to achieve more efficient and green production process.展开更多
Open channel confluences,where two streams or rivers converge,play a crucial role in hydraulic engineering and river dynamics.These confluences are characterized by complex hydrodynamics influenced by the discharge ra...Open channel confluences,where two streams or rivers converge,play a crucial role in hydraulic engineering and river dynamics.These confluences are characterized by complex hydrodynamics influenced by the discharge ratios of merging water bodies.This study investigated the mixing structure at open channel confluences using three-dimensional numerical modeling.A comprehensive three-dimensional numerical model was developed and validated against a dataset obtained from controlled laboratory experiments.This dataset incorporated three-dimensional time-averaged velocity measurements.The skew-induced and stress-induced equation systems were adopted as the core governing equations,providing a framework for simulating various scenarios.A total of ten different cases were analyzed.The results highlighted the effect of discharge ratios on turbulence,lateral and vertical vorticities,and the distribution of mixing,which intensified with higher magnitudes of discharge ratios.The mixing structure,driven by velocity gradients and vorticity,revealed the significant role of lateral and vertical vorticities in determining hydrodynamic behaviors and mixing distributions at confluences.Specifically,the momentum ratio of incoming flows governed the spatial evolution of mixing processes.This study revealed that the distribution of mixing served as a key indicator for identifying the formation of mid-channel scours.High normalized velocities induced toward the left bank led to the superelevation of the water surface,enhancing the potential for bed material and the formation of significant scour holes beneath the elevated water surface.This novel approach provides a deeper understanding of the mixing patterns at confluences,particularly in scenarios with equilibrated discharge ratios but in different magnitudes.展开更多
A new stirring method,reciprocating stirring,is developed by incorporating a periodic axial reciprocating motion into conventional stirring.This study employs computational fluid dynamics methods,utilizing volume of f...A new stirring method,reciprocating stirring,is developed by incorporating a periodic axial reciprocating motion into conventional stirring.This study employs computational fluid dynamics methods,utilizing volume of fluid and user-defined functions to control and analyze the flow field characteristics in a reciprocating stirred tank.Compared to conventional stirring,reciprocating stirring increases the overall fluid velocity by approximately 7.9%,turbulent kinetic energy(TKE)by 35.9%to 45.6%,and the turbulent dissipation rate by 10.6%to 15.7%.The primary reason is the dynamic integration of multiple flow regions,which enhances fluid interface interactions.Additionally,the study investigates the dynamic evolution of the vortex structure,uncovering the correlation between the impeller's start-stop behavior and the vortex area.The optimal impeller plate designs,forward sine-4/12D and reverse sine-5/12D,were determined based on the effective area of TKE.Reciprocating stirring,in comparison to conventional stirring,enhances secondary flow intensity by 67.3%to 93.7%and shortens mixing time by 56.6%to 173.0%.展开更多
Frequency conversion is pivotal in nonlinear optics and quantum optics for manipulating and translating light signals across different wavelength regimes.Achieving frequency conversion between two light beams with a s...Frequency conversion is pivotal in nonlinear optics and quantum optics for manipulating and translating light signals across different wavelength regimes.Achieving frequency conversion between two light beams with a small frequency interval is a central challenge.In this work,we design a pair of coupled silicon microrings wherein coupled-induced modesplitting exists to achieve a small frequency shift by the process of four-wave mixing Bragg scattering.As an example,the signal can be up or down converted to the idler which is 15.5 GHz spaced when two pumps align with another pair of split resonances.The results unveil the potential of coupled microring resonators for small interval frequency conversion in a high-fidelity,all-optical,and signal processing quantum frequency interface.展开更多
This paper focuses on the technical management of concrete mixing plants.It introduces the whole-process engineering consulting model and elaborates on multifaceted aspects of technical management,including a matrix-b...This paper focuses on the technical management of concrete mixing plants.It introduces the whole-process engineering consulting model and elaborates on multifaceted aspects of technical management,including a matrix-based management framework,standardized design management pathways,cost early-warning systems,approval strategies,regulatory databases,etc.This paper also emphasizes the importance of innovations in collaborative management mechanisms for improving quality and efficiency.展开更多
We present a theoretical study of four-wave mixing(FWM)in a degenerate two-level atomic system subject to a magnetic field whose Zeeman sublevels constitute a tripod-type atomic system,which is driven by a linearly po...We present a theoretical study of four-wave mixing(FWM)in a degenerate two-level atomic system subject to a magnetic field whose Zeeman sublevels constitute a tripod-type atomic system,which is driven by a linearly polarized field,and coupled and probed by two sets of left and right circularly polarized fields.The optical effects of coherent hole burning(CHB)and electromagnetically induced transparency(EIT)are involved in the coherent system,among which the CHB has much larger response for the FWM than the EITs.Three situations of CHB are involved,and they are the solitary CHB,overlapped CHBs,and an overlap between CHB and EIT.The overlapped CHBs have the greatest magnitude of FWM signal among the three situations.Whereas,for the overlapped CHB and EIT,it has the smallest FWM magnitude,which is no more than one tenth of the former.While for the single CHB,the FWM magnitude is half of that of the overlapped CHBs.It is noted that,in the overlap between CHB and EIT,dual EIAs can be obtained,whose FWM signal also has an enhancement in comparison to no EIA.展开更多
The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed wit...The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed with the hydrological and microstructure observations conducted in summer 2012 in the shelf sea east of Hainan Island, in South China Sea(SCS). The deep neural network model is used and incorporates the Richardson number Ri, the normalized depth D, the horizontal velocity speed U, the shear S^(2), the stratification N^(2), and the density ρ as input parameters. Comparing to the scheme without parameter D and region division, the depth-dependent scheme improves the prediction of the turbulent kinetic energy dissipation rate ε. The correlation coefficient(r) between predicted and observed lgε increases from 0.49 to 0.62, and the root mean square error decreases from 0.56 to 0.48. Comparing to the traditional physics-driven parameterization schemes, such as the G89 and MG03, the data-driven approach achieves higher accuracy and generalization. The SHapley Additive Explanations(SHAP) framework analysis reveals the importance descending order of the input parameters as: ρ, D, U, N^(2), S^(2), and Ri in the whole depth, while D is most important in the upper and bottom boundary layers(D≤0.3&D≥0.65) and least important in middle layer(0.3<D<0.65). The research shows applicability of constructing deep learning-based ocean turbulent mixing parameterization schemes using limited observational data and well-established physical processes.展开更多
This paper is devoted to proving the polynomial mixing for a weakly damped stochastic nonlinear Schröodinger equation with additive noise on a 1D bounded domain.The noise is white in time and smooth in space.We c...This paper is devoted to proving the polynomial mixing for a weakly damped stochastic nonlinear Schröodinger equation with additive noise on a 1D bounded domain.The noise is white in time and smooth in space.We consider both focusing and defocusing nonlinearities,with exponents of the nonlinearityσ∈[0,2)andσ∈[0,∞),and prove the polynomial mixing which implies the uniqueness of the invariant measure by using a coupling method.In the focusing case,our result generalizes the earlier results in[12],whereσ=1.展开更多
Temporal optics,which enables lossless manipulation of ultrafast pulses,offers a new dimension for the regulation of quantum optical fields.In this paper,we established a temporal Fourier transform(TF)system based on ...Temporal optics,which enables lossless manipulation of ultrafast pulses,offers a new dimension for the regulation of quantum optical fields.In this paper,we established a temporal Fourier transform(TF)system based on a four-wave mixing(FWM)time lens and constructed a full quantum theoretical model for the resulting temporal SU(1,1)interferometer.This interferometer has high temporal resolution,can impose interference in both time and frequency domains,and is sensitive to the phase derivative.By introducing linear time-varying phase modulation,we achieved sub-picosecond precision in temporal autocorrelation measurements and generatedan optical frequency comb with a fixed interval based on a feedback iteration mechanism.Theoretical analysis revealsthe crucial regulatory role of time-frequency coupling in quantum interference,providing novel solutions for ultrafast quantum imaging,temporal mode encoding,and the generation of optical frequency quantization.展开更多
In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the d...In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.展开更多
Ni-rich cathodes(Ni≥70%)with high specific capacities emerge as promising candidates for long-range lithium-ion batteries(LIBs).Nevertheless,their practical application is severely limited by two unresolved challenge...Ni-rich cathodes(Ni≥70%)with high specific capacities emerge as promising candidates for long-range lithium-ion batteries(LIBs).Nevertheless,their practical application is severely limited by two unresolved challenges:structural degradation from uncontrolled Li/Ni mixing and interfacial instability exacerbated by air/electrolyte corrosion.Herein,we propose a dual-modulation strategy to synthesize a stable Ni-rich cathode via carboxylate-based metal-organic frameworks(MOFs)-derived precursors,whereby oxygen vacancies in the precursors induce controlled moderate Li/Ni mixing,while their enhanced specific-surface-area property enables dense amorphous Li_(2)CO_(3)encapsulation.The optimal Li/Ni mixing harnesses the Ni pillar effect to stabilize the structure of cathodes upon cycling.Additionally,amorphous Li_(2)CO_(3)coating serves not only as a thermodynamically stable and air-impermeable protective layer for the cathodes,but as a transformative precursor for an F-rich cathode electrolyte interphase(CEI)which enhances interfacial stability and electrochemical properties.This dual-modulated cathode delivers a high discharge capacity of 215.1 mA h g^(-1)at 0.1 C,retains 84.9% capacity after 200 cycles at 1 C in half cells,and achieves 96.0 mA h g^(-1)at 8 C in full-cell tests.Furthermore,we unravel the potential mechanism of Ni pillar effect from optimal Li/Ni mixing and track the evolution mechanism of Li_(2)CO_(3)coating into F-rich CEI.This work offers advanced perspectives for the controllable cation disordering engineering and rational design of surface residual lithium compounds in Ni-rich cathodes,thereby providing new guiding principles for protecting high-capacity cathodes in energy storage devices.展开更多
Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal activities.Cybercriminals generally legalize illicit funds by Bitcoin mixing services.Therefore,it is critical to investigate...Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal activities.Cybercriminals generally legalize illicit funds by Bitcoin mixing services.Therefore,it is critical to investigate the mixing services in cryptocurrency anti-money laundering.Existing studies treat different mixing services as a class of suspicious Bitcoin entities.Furthermore,they are limited by relying on expert experience or needing to deal with large-scale networks.So far,multi-class mixing service identification has not been explored yet.It is challenging since mixing services share a similar procedure,presenting no sharp distinctions.However,mixing service identification facilitates the healthy development of Bitcoin,supports financial forensics for cryptocurrency regulation and legislation,and provides technical means for fine-grained blockchain supervision.This paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification(BMSI-GC)model.First,BMSI-GC constructs 2-hop ego networks(2-egonets)of mixing services based on their historical transactions.Second,it applies graph2vec,a graph classification model mainly used to calculate the similarity between graphs,to automatically extract address features from the constructed 2-egonets.Finally,it trains a multilayer perceptron classifier to perform classification based on the extracted features.BMSI-GC is flexible without handling the full-size network and handcrafting address features.Moreover,the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for identification.Our experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification,achieving an average identification F1-score of 95.08%.展开更多
The exponential growth of the Internet of Things(IoT)has introduced significant security challenges,with zero-day attacks emerging as one of the most critical and challenging threats.Traditional Machine Learning(ML)an...The exponential growth of the Internet of Things(IoT)has introduced significant security challenges,with zero-day attacks emerging as one of the most critical and challenging threats.Traditional Machine Learning(ML)and Deep Learning(DL)techniques have demonstrated promising early detection capabilities.However,their effectiveness is limited when handling the vast volumes of IoT-generated data due to scalability constraints,high computational costs,and the costly time-intensive process of data labeling.To address these challenges,this study proposes a Federated Learning(FL)framework that leverages collaborative and hybrid supervised learning to enhance cyber threat detection in IoT networks.By employing Deep Neural Networks(DNNs)and decentralized model training,the approach reduces computational complexity while improving detection accuracy.The proposed model demonstrates robust performance,achieving accuracies of 94.34%,99.95%,and 87.94%on the publicly available kitsune,Bot-IoT,and UNSW-NB15 datasets,respectively.Furthermore,its ability to detect zero-day attacks is validated through evaluations on two additional benchmark datasets,TON-IoT and IoT-23,using a Deep Federated Learning(DFL)framework,underscoring the generalization and effectiveness of the model in heterogeneous and decentralized IoT environments.Experimental results demonstrate superior performance over existing methods,establishing the proposed framework as an efficient and scalable solution for IoT security.展开更多
Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often stru...Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.展开更多
基金supported by the National Natural Science Foundation of China(22288102,22035007,and 22122815)。
文摘The mixing process plays a pivotal role in the design,optimization,and scale-up of chemical reactors.For most chemical reactions,achieving uniform and rapid contact between reactants at the molecular level is crucial.Mixing intensification encompasses innovative methods and tools that address the limitations of inadequate mixing within reactors,enabling efficient reaction scaling and boosting the productivity of industrial processes.This review provides a concise introduction to the fundamentals of multiphase mixing,followed by case studies highlighting the application of mixing intensification in the production of energy-storage materials,advanced optical materials,and nanopesticides.These examples illustrate the significance of theoretical analysis in informing and advancing engineering practices within the chemical industry.We also explore the challenges and opportunities in this field,offering insights based on our current understanding.
基金financially supported by the Fundamental Research Funds for the Central Universities(Grant No.30923011018)。
文摘The present study introduces a screw-pressing charging method to tackle deficiencies in automation and charge uniformity during the melt-casting of polymer-based energetic materials.To ensure the safety of the experiments,this study used inert materials with similar physical properties to partially substitute for the actual energetic components in the preparation of simulant materials.By thoroughly analyzing slurry physical properties,a simulation framework and an extensive performance evaluation method were developed.Such tools guide the design of the structure and configuration of process parameters.Results demonstrate that employing the Pin element significantly enhances radial mixing within the screw,minimizes temperature variations in the slurry,and improves both efficiency and safety in the mixing process.Further,adjustments such as widening the cone angle of the barrel,modifying the solid content of the slurry,and varying the speed of the screw can optimize the mechanical and thermal coupling in the flow field.These adjustments promote higher-quality slurry and create a safer production environment for the extrusion process.
基金supported by the National Key R&D Program of China(2022YFB3803501)the National Natural Science Foundation of China(22179008,22209156)+5 种基金support from the Beijing Nova Program(20230484241)support from the China Postdoctoral Science Foundation(2024M754084)the Postdoctoral Fellowship Program of CPSF(GZB20230931)support from beamline BL08U1A of Shanghai Synchrotron Radiation Facility(2024-SSRF-PT-506950)beamline 1W1B of the Beijing Synchrotron Radiation Facility(2021-BEPC-PT-006276)support from Initial Energy Science&Technology Co.,Ltd(IEST)。
文摘The implementation of ultrahigh-Ni cathodes in high-energy lithium-ion batteries(LIBs)is constrained by significant structural and interfacial degradation during cycling.In this study,doping-induced surface restructuring in ultrahigh-nickel cathode materials is rapidly facilitated through an ultrafast Joule heating method.Density functional theory(DFT)calculations,synchrotron X-ray absorption spectroscopy(XAS),and single-particle force test confirmed the establishment of a stable crystal framework and lattice oxygen,which mitigated H2-H3 phase transitions and improved structural reversibility.Additionally,the Sc doping process exhibits a pinning effect on the grain boundaries,as shown by scanning transmission electron microscopy(STEM),enhancing Li~+diffusion kinetics and decreasing mechanical strain during cycling.The in situ development of a cation-mixing layer at grain boundaries also creates a robust cathode/electrolyte interphase,effectively reducing interfacial parasitic reactions and transition metal dissolution,as validated by STEM and time-of-flight secondary ion mass spectrometry(TOF-SIMS).These synergistic modifications reduce particle cracking and surface/interface degradation,leading to enhanced rate capability,structural integrity,and thermal stability.Consequently,the optimized Sc-modified ultrahigh-Ni cathode(Sc-1)exhibits 93.99%capacity retention after 100 cycles at 1 C(25℃)and87.06%capacity retention after 100 cycles at 1 C(50℃),indicating excellent cycling and thermal stability.By presenting a one-step multifunctional modification approach,this research delivers an extensive analysis of the mechanisms governing the structure,microstructure,and interface properties of nickel-rich layered cathode materials(NCMs).These results underscore the potential of ultrahigh-Ni cathodes as viable candidates for advanced lithium-ion batteries(LIBs)in next-generation electric vehicles(EVs).
基金supported by the National Key R&D Program of China(Grant No.2023YFA1608400)the National Natural Science Foundation of China(Grant Nos.12205275 and 12588301).
文摘A reshock experiment for investigating the growth of material mixing driven by the Richtmyer–Meshkov instability has been conducted at the SG 100 kJ Laser Facility.We present a novel measurement technique for capturing the density field and the temporal evolution of the mixing width in rough aluminum subjected to reshocks under extreme conditions.The temporal evolution of the aluminum layer width obtained from backlit X-ray radiography demonstrates a sharp increase in width caused by reshocks,and simulations using the BHR-2 turbulent mixing model show excellent agreement with the measured aluminum layer width.Moreover,by utilizing a quasi-monochromatic X-ray imaging system at 5.2 keV,based on Bragg reflection from a spherically curved quartz crystal,we demonstrate direct quantification of the aluminum density field in mixed regions for the first time in a indirectly driven reshock experiment.The deviation between the calculated and actual density values is significantly less than 10%when the density of the aluminum region is below 0.7 g/cm3.The density field provides further information about variable-density turbulent mixing,which improves the constraints on simulations and enhances predictive capabilities for inertial confinement fusion target design and astrophysical shock scenarios.
基金supported by the National Natural Science Foundation of China(U22A20429 and 22308103)Shanghai Pilot Program for Basic Research(22TQ1400100-13)+2 种基金Postdoctoral Fellowship Program of CPSF(GZB20230214)China Postdoctoral Science Foundation(2023M731083)the Fundamental Research Funds for the Central Universities.
文摘Developing cost-effective single-crystalline Ni-rich Co-poor cathodes operating at high-voltage is one of the most important ways to achieve higher energy Li-ion batteries. However, the Li/O loss and Li/Ni mixing under high-temperature lithiation result in electrochemical kinetic hysteresis and structural instability. Herein, we report a highly-ordered single-crystalline LiNi0.85Co0.05Mn0.10O2(NCM85) cathode by doping K+and F-ions. To be specific, the K-ion as a fluxing agent can remarkably decrease the solid-state lithiation temperature by ~30°C, leading to less Li/Ni mixing and oxygen vacancy. Meanwhile, the strong transitional metal(TM)-F bonds are helpful for enhancing de-/lithiation kinetics and limiting the lattice oxygen escape even at 4.5 V high-voltage. Their advantages synergistically endow the single-crystalline NCM85 cathode with a very high reversible capacity of 222.3 mAh g-1. A superior capacity retention of 91.3% is obtained after 500 times at 1 C in pouch-type full cells, and a prediction value of 75.3% is given after cycling for 5000 h. These findings are reckoned to expedite the exploitation and application of high-voltage single-crystalline Ni-rich cathodes for next-generation Li-ion batteries.
基金supported by the National Natural Science Foundation of China(52025103)the Xplorer Prize(XPLORER-2022-1034).
文摘In petroleum,mercaptan impurities generate malodorous fumes that pose risks to both human health and the environment,and leading to substandard oil quality.Lye desulfurization is a widely employed technique for eliminating mercaptans from oil.In traditional scrubber towers,lye and oil are poorly mixed,the desulfurization efficiency is low,and the lye consumption is high.To enhance washing efficiency,a droplet micromixer and corresponding fiber coalescence separator were developed.By optimizing the structure and operating parameters,more effective mixing and separation were achieved,and both caustic washing and desulfurization were enhanced.The proposed mixer/separator outperforms the industry standard by reducing the caustic loading by 30%and offers superior economic and engineering performances.The results of this study offer a direction for designing and optimizing a mercaptan removal unit to enhance the scrubbing effectiveness and decrease expenses to achieve more efficient and green production process.
文摘Open channel confluences,where two streams or rivers converge,play a crucial role in hydraulic engineering and river dynamics.These confluences are characterized by complex hydrodynamics influenced by the discharge ratios of merging water bodies.This study investigated the mixing structure at open channel confluences using three-dimensional numerical modeling.A comprehensive three-dimensional numerical model was developed and validated against a dataset obtained from controlled laboratory experiments.This dataset incorporated three-dimensional time-averaged velocity measurements.The skew-induced and stress-induced equation systems were adopted as the core governing equations,providing a framework for simulating various scenarios.A total of ten different cases were analyzed.The results highlighted the effect of discharge ratios on turbulence,lateral and vertical vorticities,and the distribution of mixing,which intensified with higher magnitudes of discharge ratios.The mixing structure,driven by velocity gradients and vorticity,revealed the significant role of lateral and vertical vorticities in determining hydrodynamic behaviors and mixing distributions at confluences.Specifically,the momentum ratio of incoming flows governed the spatial evolution of mixing processes.This study revealed that the distribution of mixing served as a key indicator for identifying the formation of mid-channel scours.High normalized velocities induced toward the left bank led to the superelevation of the water surface,enhancing the potential for bed material and the formation of significant scour holes beneath the elevated water surface.This novel approach provides a deeper understanding of the mixing patterns at confluences,particularly in scenarios with equilibrated discharge ratios but in different magnitudes.
基金National Key Research and Development Program of China(2022YFC3902000)Yunnan Major Scientific and Technological Projects(202202AG050002,202202AG050007)National Natural Science Foundation of China(52166004).
文摘A new stirring method,reciprocating stirring,is developed by incorporating a periodic axial reciprocating motion into conventional stirring.This study employs computational fluid dynamics methods,utilizing volume of fluid and user-defined functions to control and analyze the flow field characteristics in a reciprocating stirred tank.Compared to conventional stirring,reciprocating stirring increases the overall fluid velocity by approximately 7.9%,turbulent kinetic energy(TKE)by 35.9%to 45.6%,and the turbulent dissipation rate by 10.6%to 15.7%.The primary reason is the dynamic integration of multiple flow regions,which enhances fluid interface interactions.Additionally,the study investigates the dynamic evolution of the vortex structure,uncovering the correlation between the impeller's start-stop behavior and the vortex area.The optimal impeller plate designs,forward sine-4/12D and reverse sine-5/12D,were determined based on the effective area of TKE.Reciprocating stirring,in comparison to conventional stirring,enhances secondary flow intensity by 67.3%to 93.7%and shortens mixing time by 56.6%to 173.0%.
基金Project supported by the National Key Research and Development Program of China(Grant No.2022YFF0712800)。
文摘Frequency conversion is pivotal in nonlinear optics and quantum optics for manipulating and translating light signals across different wavelength regimes.Achieving frequency conversion between two light beams with a small frequency interval is a central challenge.In this work,we design a pair of coupled silicon microrings wherein coupled-induced modesplitting exists to achieve a small frequency shift by the process of four-wave mixing Bragg scattering.As an example,the signal can be up or down converted to the idler which is 15.5 GHz spaced when two pumps align with another pair of split resonances.The results unveil the potential of coupled microring resonators for small interval frequency conversion in a high-fidelity,all-optical,and signal processing quantum frequency interface.
文摘This paper focuses on the technical management of concrete mixing plants.It introduces the whole-process engineering consulting model and elaborates on multifaceted aspects of technical management,including a matrix-based management framework,standardized design management pathways,cost early-warning systems,approval strategies,regulatory databases,etc.This paper also emphasizes the importance of innovations in collaborative management mechanisms for improving quality and efficiency.
基金supported by the Open Subject of the State Key Laboratory of Quantum Optics and Quantum Optics Devices(Grant No.KF202209).
文摘We present a theoretical study of four-wave mixing(FWM)in a degenerate two-level atomic system subject to a magnetic field whose Zeeman sublevels constitute a tripod-type atomic system,which is driven by a linearly polarized field,and coupled and probed by two sets of left and right circularly polarized fields.The optical effects of coherent hole burning(CHB)and electromagnetically induced transparency(EIT)are involved in the coherent system,among which the CHB has much larger response for the FWM than the EITs.Three situations of CHB are involved,and they are the solitary CHB,overlapped CHBs,and an overlap between CHB and EIT.The overlapped CHBs have the greatest magnitude of FWM signal among the three situations.Whereas,for the overlapped CHB and EIT,it has the smallest FWM magnitude,which is no more than one tenth of the former.While for the single CHB,the FWM magnitude is half of that of the overlapped CHBs.It is noted that,in the overlap between CHB and EIT,dual EIAs can be obtained,whose FWM signal also has an enhancement in comparison to no EIA.
基金Supported by the National Natural Science Foundation of China(No.42276019)the Guangdong Provincial Observation and Research Station for Tropical Ocean Environment in Western Coastal Waters(No.GSTOEW)。
文摘The uncertainty of ocean turbulent mixing parameterization comprises a significant challenge in ocean and climate models. A depth-dependent deep learning ocean turbulent mixing parameterization scheme was proposed with the hydrological and microstructure observations conducted in summer 2012 in the shelf sea east of Hainan Island, in South China Sea(SCS). The deep neural network model is used and incorporates the Richardson number Ri, the normalized depth D, the horizontal velocity speed U, the shear S^(2), the stratification N^(2), and the density ρ as input parameters. Comparing to the scheme without parameter D and region division, the depth-dependent scheme improves the prediction of the turbulent kinetic energy dissipation rate ε. The correlation coefficient(r) between predicted and observed lgε increases from 0.49 to 0.62, and the root mean square error decreases from 0.56 to 0.48. Comparing to the traditional physics-driven parameterization schemes, such as the G89 and MG03, the data-driven approach achieves higher accuracy and generalization. The SHapley Additive Explanations(SHAP) framework analysis reveals the importance descending order of the input parameters as: ρ, D, U, N^(2), S^(2), and Ri in the whole depth, while D is most important in the upper and bottom boundary layers(D≤0.3&D≥0.65) and least important in middle layer(0.3<D<0.65). The research shows applicability of constructing deep learning-based ocean turbulent mixing parameterization schemes using limited observational data and well-established physical processes.
基金supported by the National Key R&D Program of China(2023YFA1009200)the NSFC(11925102)the Liaoning Revitalization Talents Program(XLYC2202042)。
文摘This paper is devoted to proving the polynomial mixing for a weakly damped stochastic nonlinear Schröodinger equation with additive noise on a 1D bounded domain.The noise is white in time and smooth in space.We consider both focusing and defocusing nonlinearities,with exponents of the nonlinearityσ∈[0,2)andσ∈[0,∞),and prove the polynomial mixing which implies the uniqueness of the invariant measure by using a coupling method.In the focusing case,our result generalizes the earlier results in[12],whereσ=1.
文摘Temporal optics,which enables lossless manipulation of ultrafast pulses,offers a new dimension for the regulation of quantum optical fields.In this paper,we established a temporal Fourier transform(TF)system based on a four-wave mixing(FWM)time lens and constructed a full quantum theoretical model for the resulting temporal SU(1,1)interferometer.This interferometer has high temporal resolution,can impose interference in both time and frequency domains,and is sensitive to the phase derivative.By introducing linear time-varying phase modulation,we achieved sub-picosecond precision in temporal autocorrelation measurements and generatedan optical frequency comb with a fixed interval based on a feedback iteration mechanism.Theoretical analysis revealsthe crucial regulatory role of time-frequency coupling in quantum interference,providing novel solutions for ultrafast quantum imaging,temporal mode encoding,and the generation of optical frequency quantization.
文摘In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.
基金the financial support from the Special Funds for the Cultivation of Guangdong College Students’Scientific and Technological Innovation(“Climbing Program”Special Funds,pdjh2024a109)。
文摘Ni-rich cathodes(Ni≥70%)with high specific capacities emerge as promising candidates for long-range lithium-ion batteries(LIBs).Nevertheless,their practical application is severely limited by two unresolved challenges:structural degradation from uncontrolled Li/Ni mixing and interfacial instability exacerbated by air/electrolyte corrosion.Herein,we propose a dual-modulation strategy to synthesize a stable Ni-rich cathode via carboxylate-based metal-organic frameworks(MOFs)-derived precursors,whereby oxygen vacancies in the precursors induce controlled moderate Li/Ni mixing,while their enhanced specific-surface-area property enables dense amorphous Li_(2)CO_(3)encapsulation.The optimal Li/Ni mixing harnesses the Ni pillar effect to stabilize the structure of cathodes upon cycling.Additionally,amorphous Li_(2)CO_(3)coating serves not only as a thermodynamically stable and air-impermeable protective layer for the cathodes,but as a transformative precursor for an F-rich cathode electrolyte interphase(CEI)which enhances interfacial stability and electrochemical properties.This dual-modulated cathode delivers a high discharge capacity of 215.1 mA h g^(-1)at 0.1 C,retains 84.9% capacity after 200 cycles at 1 C in half cells,and achieves 96.0 mA h g^(-1)at 8 C in full-cell tests.Furthermore,we unravel the potential mechanism of Ni pillar effect from optimal Li/Ni mixing and track the evolution mechanism of Li_(2)CO_(3)coating into F-rich CEI.This work offers advanced perspectives for the controllable cation disordering engineering and rational design of surface residual lithium compounds in Ni-rich cathodes,thereby providing new guiding principles for protecting high-capacity cathodes in energy storage devices.
基金supported in part by National Key R&D Program of China under Grant 2023YFB3106801in part by Jiangsu Province Natural Science Foundation Project under Grant BK20231413+1 种基金in part by the National Natural Science Foundation of China under Grants 61602114 and 62172093in part by the Special Funds for Basic Scientific Research Operations of Central Universities under Grant 2242024K30021。
文摘Due to its anonymity and decentralization,Bitcoin has long been a haven for various illegal activities.Cybercriminals generally legalize illicit funds by Bitcoin mixing services.Therefore,it is critical to investigate the mixing services in cryptocurrency anti-money laundering.Existing studies treat different mixing services as a class of suspicious Bitcoin entities.Furthermore,they are limited by relying on expert experience or needing to deal with large-scale networks.So far,multi-class mixing service identification has not been explored yet.It is challenging since mixing services share a similar procedure,presenting no sharp distinctions.However,mixing service identification facilitates the healthy development of Bitcoin,supports financial forensics for cryptocurrency regulation and legislation,and provides technical means for fine-grained blockchain supervision.This paper aims to achieve multi-class Bitcoin Mixing Service Identification with a Graph Classification(BMSI-GC)model.First,BMSI-GC constructs 2-hop ego networks(2-egonets)of mixing services based on their historical transactions.Second,it applies graph2vec,a graph classification model mainly used to calculate the similarity between graphs,to automatically extract address features from the constructed 2-egonets.Finally,it trains a multilayer perceptron classifier to perform classification based on the extracted features.BMSI-GC is flexible without handling the full-size network and handcrafting address features.Moreover,the differences in transaction patterns of mixing services reflected in the 2-egonets provide adequate information for identification.Our experimental study demonstrates that BMSI-GC performs excellently in multi-class Bitcoin mixing service identification,achieving an average identification F1-score of 95.08%.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2025R97)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The exponential growth of the Internet of Things(IoT)has introduced significant security challenges,with zero-day attacks emerging as one of the most critical and challenging threats.Traditional Machine Learning(ML)and Deep Learning(DL)techniques have demonstrated promising early detection capabilities.However,their effectiveness is limited when handling the vast volumes of IoT-generated data due to scalability constraints,high computational costs,and the costly time-intensive process of data labeling.To address these challenges,this study proposes a Federated Learning(FL)framework that leverages collaborative and hybrid supervised learning to enhance cyber threat detection in IoT networks.By employing Deep Neural Networks(DNNs)and decentralized model training,the approach reduces computational complexity while improving detection accuracy.The proposed model demonstrates robust performance,achieving accuracies of 94.34%,99.95%,and 87.94%on the publicly available kitsune,Bot-IoT,and UNSW-NB15 datasets,respectively.Furthermore,its ability to detect zero-day attacks is validated through evaluations on two additional benchmark datasets,TON-IoT and IoT-23,using a Deep Federated Learning(DFL)framework,underscoring the generalization and effectiveness of the model in heterogeneous and decentralized IoT environments.Experimental results demonstrate superior performance over existing methods,establishing the proposed framework as an efficient and scalable solution for IoT security.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2025-02-01295).
文摘Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.
